Motivation for this article is to discuss a few Natural Language Processing (NLP) models & exciting developments in that space, and to showcase implementations for those models.

Growing up, I was glued to my Television set whenever there was a match between Martina Navratilova, a seasoned champion, and Steffi Graf, a budding one (and my celebrity crush). Martina was ubiquitous while Steffi was promising, rearing her head to become the new champ. The duel between NLP models mirror their rivalry, and is now what keeps me glued these days.

RNN Everywhere

Like Martina, until recently Recurrent Neural Network (RNN’s) was everywhere and…

The purpose of this article is to emphasize how transfer learning can help enterprises kick-start their ML implementations. An example using Keras and its pre-trained model is given for demonstration purposes.

Imagine, if we were not able to take our learning from one situation to another. How would our world look like?

As humans, we learn new things and as we learn more, we apply what we have learnt already. Our school system is built on the same principle — What we learn in prior grades sets the foundation for next.

The Question is — Can the machines do the…

Ninja is the word that comes to mind as I begin to write this blog and look back at what I have done so far.

A Ninja is one who operates with great grace and ease, to the point of making what they do seem simple. It is only after hours, days, weeks, months, and years, however, when one can finally reach this level.

A few years ago, my thoughts about Machine learning were different from what they are now. I perceived Machine learning as convoluted and treacherous, with its emphasis on Advanced Math, and its vast expanses. …